NDVI

NDVI is by far the most commonly used vegetation index. NDVI was developed in the early seventies (Rouse 1973, Tucker 1979), and widely used with remote sensing in the nineties until now. It is computed from the surface reflectance in the red and near infra-red channels on each side of the red-edge.

where and are reflectances in the NIR and RED. Although several users still use top-of atmosphere reflectances (TOA), surface reflectances should be used to reduce sensitivity to variations of aerosol atmospheric content.

A time profile of surface reflectance from Sentinel2 satellite for the blue, green, red and NIR spectral bands for a summer crop in South East France. The observation under constant viewing angles minimizes directional effects.One can also notice that reflectance variations related to vegetation status are greater in the near infra-red, while the noise is usually lower. As a result, a vegetation index should rely more on the NIR than on the red.

I think NDVI is mainly used for the following reasons (but feel free to comment and add your reasons) :

it has the large advantage of qualifying the vegetation status with only one dimension, instead of N dimensions if we consider the reflectances of each channel. Of course, by replacing N dimensions by only one, a lot of information is lost.

it enables to reduce the temporal noise due to directional effects. But with the Landsat, Sentinel-2 or Venµs satellites, which observe under constant viewing angles, the directional effects have been considerably reduced.

I therefore tend to tell students that if NDVI is convenient, it is not the only way to monitor vegetation.

As you probably know, PEPS is the French Collaborative ground segment for Copernicus Sentinel program. And, first of all, it is a mirror site that distributes all the Sentinel data in near real time. These last weeks, real time was not available for Sentinel-2, as the data format and structure of Sentinel-2 products had deeply changed, and the software needed adaptation. PEPS team created a new collection, named "Sentinel-2 Single Tiles", coded "S2ST" to separate the old format from the new one. Now that the new version has been installed and validated, the PEPS mirror site is once again up to date.

The production of Sentinel-2 L2A data is on-going at CNES THEIA, but it is still a little slower than expected. We had one fast day on which the exploitation team managed to process 600 tiles, but the production has often been slower as we needed to solve a few glitches, and as the whole CNES processing center had also its own issues.

Meanwhile, my colleagues at CNES MUSCATE Center, with the precious help of Dominique Clesse (CAP GEMINI) and Remi Mourembles (CAP GEMINI), have implemented the possibility to download the images via a script and no click. By the way, the shop cart, which did not work when we ordered more than 10 products has also been repaired.

The script is very easy to use, for instance, the following line downloads the SENTINEL-2 products above tile T31TCJ (Toulouse), acquired in September 2016 :

You already heard about iota2 processor, and you must know that it can process LANDSAT 8 time series et deliver land cover maps for whole countries. These las days, Arthur Vincent completed the code that allows processing Sentinel-2 time series. Even if atmospherically corrected Sentinel-2 data are not yet available above the whole France, we used the demonstration products delivered by Theia to test our processor.

Everything seems to work fine, and the 10 m resolution of Sentinel-2 seems to allow seeing much more details. The joined images show two extracts near Avignon, in Provence, which show the differences between Landsat 8 and Sentinel-2. Please just look only at the detail level, and not at the differences in terms of classes. Both maps were produces using different time periods, and a period limited to winter and beginning of spring for Sentinel-2, and the learning database is also different. Please don,'t draw conclusions too fast about the thematic quality of the maps.

"well, after all you are probably right, but don't worry, we only use it to do quick and dirty stuff, not real scientific work"

As most (...) of these colleagues are quite sensible, I am not worrying too much. But as far as I am concerned, I would have some chances to be a victim of Mrs-Armitage-on-wheels Syndrom (AWS). I guess I do not need to explain it to our british colleagues who consult this blog, this syndrom originates form the great children book from Quentin Blake, that I used to read to my children, some time ago (every night for the two first weeks, then once in a while...) : Mrs Armitage on wheels. Another daddy reads it for you here.

Exceptional rainfall in May caused heavy flooding in the Paris region. Newspapers and TVs reported that the Seine flood forced the Louvre staff to move away from rising waters the art pieces that were stored in their cellar. But they did not tell you that about 50 km east of the Louvre museum, the flood of the Grand Morin river in Coulommiers also inundated the cellar of my parents-in-law. I'm really concerned about this cellar because I care about my parents-in-law of course, and also because I have let some of my bottles of wine in their cellar. Continue reading

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